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How widespread use of generative AI for images and video can affect the environment and the science of ecology.
Rillig, Matthias C; Mansour, India; Hempel, Stefan; Bi, Mohan; König-Ries, Birgitta; Kasirzadeh, Atoosa.
Afiliação
  • Rillig MC; Institute of Biology, Freie Universität Berlin, Berlin, Germany.
  • Mansour I; Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany.
  • Hempel S; Institute of Biology, Freie Universität Berlin, Berlin, Germany.
  • Bi M; Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany.
  • König-Ries B; Institute of Biology, Freie Universität Berlin, Berlin, Germany.
  • Kasirzadeh A; Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany.
Ecol Lett ; 27(3): e14397, 2024 Mar.
Article em En | MEDLINE | ID: mdl-38430051
ABSTRACT
Generative artificial intelligence (AI) models will have broad impacts on society including the scientific enterprise; ecology and environmental science will be no exception. Here, we discuss the potential opportunities and risks of advanced generative AI for visual material (images and video) for the science of ecology and the environment itself. There are clearly opportunities for positive impacts, related to improved communication, for example; we also see possibilities for ecological research to benefit from generative AI (e.g., image gap filling, biodiversity surveys, and improved citizen science). However, there are also risks, threatening to undermine the credibility of our science, mostly related to actions of bad actors, for example in terms of spreading fake information or committing fraud. Risks need to be mitigated at the level of government regulatory measures, but we also highlight what can be done right now, including discussing issues with the next generation of ecologists and transforming towards radically open science workflows.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Biodiversidade Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Biodiversidade Idioma: En Ano de publicação: 2024 Tipo de documento: Article